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Conditioning and grouping are two important concepts in graphing that allow us to rapidly refine our understanding of data under consideration. Conditioning, in particular, allows us to view relationships across “panels” with common scales. Each panel contains a plot whose data is “conditional” upon records drawn from the category that supports that particular panel (an

Conditioning and grouping are two important concepts in graphing that allow us to rapidly refine our understanding of data under consideration. Conditioning, in particular, allows us to view relationships across “panels” with common scales. Each panel contains a plot whose data is “conditional” upon records drawn from the category that supports that particular panel (an

In my last post I talked about using the number of lines in a function as a guide to whether you need to break it down into smaller pieces. There are many other useful metrics for the complexity of a function, most notably cyclomatic complexity, which tracks the number of different routes that code can

It’s widely considered good programming practice to have lots of little functions rather than a few big functions. The reasons behind this are simple. When your program breaks, it’s much nicer to debug a five line function than a five hundred line function. Additionally, by breaking up your code into little chunks, you often find

The R programming language includes many abbreviations. Abbreviations exist in function names, argument names, and allowed values for arguments. This post expands on over 150 R abbreviations with the aim of making it easier for users new to R who are trying...

The R programming language includes many abbreviations. Abbreviations exist in function names, argument names, and allowed values for arguments. This post expands on over 150 R abbreviations with the aim of making it easier for users new to R who are trying...

There are many types of scatterplots in R, here are some examples based on the famous Iris data.pairs() and coplot() in package graphics.gpairs() in package YaleToolkit.scatterplot.matrix() or spm() in package car.splom() in package lattice.

There are many types of scatterplots in R, here are some examples based on the famous Iris data.pairs() and coplot() in package graphics.gpairs() in package YaleToolkit.scatterplot.matrix() or spm() in package car.splom() in package lattice.